Development of a technique for achieving an optimum BSFC for LAF engine

The reserves of gasoline and diesel fuels are ever decreasing, which plays an important role in the technological development of automobiles. Numerous countries, especially the United States, wish to slowly decrease their fuel dependence on other countries by producing in house renewable fuels like biodiesels or ethanol. Therefore, the new automobile engines have to successfully run on a variety of fuels without significant changes to their designs. The current study focuses on assessing the potential of ethanol fuels to improve the performance of 'flex-fuel SI engines,' which literally means 'engines that are flexible in their fuel requirement.' Another important area within spark ignition (SI) engine research is the implementation of new technologies like Variable Valve Timing (VVT) or Variable Compression Ratio (VCR) to improve engine performance. These technologies add more complexity to the original system by adding extra degrees of freedom. Therefore, the potential of these technologies has to be evaluated before they are installed in any SI engine. The current study focuses on evaluating the advantages and drawbacks of these technologies, primarily from an engine brake efficiency perspective. The results show a significant improvement in engine efficiency with the use of VVT and VCR together. Spark ignition engines always operate at a lower compression ratio as compared to compression ignition (CI) engines primarily due to knock constraints. Therefore, even if the use of a higher compression ratio would result in a significant improvement in SI engine efficiency, the engine may still operate at a lower compression ratio due to knock limitations. Ethanol fuels extend the knock limit making the use of higher compression ratios possible. Hence, the current study focuses on using VVT, VCR, and ethanol-gasoline blends to improve overall engine performance. The results show that these technologies promise definite engine performance improvements provided both their positive and negative potentials have been evaluated prior to installation.

DESIGN AND DEVELOPMENT OF BODIPY-BASED FLUORESCENT PROBES FOR SENSING AND IMAGING OF CYANIDE, Zn (II) IONS, LYSOSOMAL pH AND CANCER CELLS

BODIPY (4,4-Difluoro-3a,4a-diaza-s-indacene) dyes have gained lots of attention in application of fluorescence sensing and imaging in recent years because they possess many distinctive and desirable properties such as high extinction coefficient, narrow absorption and emission bands, high quantum yield and low photobleaching effect. However, most of BODIPY-based fluorescent probes have very poor solubilities in aqueous solution, emit less than 650 nm fluorescence that can cause cell and tissue photodamages compared with bio-desirable near infrared (650-900 nm) light. These undesirable properties extremely limit the applications of BODIPY-based fluorescent probes in sensing and imaging applications. In order to overcome these drawbacks, we have developed a very effective strategy to prepare a series of neutral highly water- soluble BODIPY dyes by enhancing the water solubilities of BODIPY dyes via incorporation of tri(ethylene glycol)methyl ether (TEG) and branched oligo(ethylene glycol)methyl ether (BEG) residues onto BODIPY dyes at 1,7-, 2,6-, 3,5-, 4- and meso- positions. We also have effectively tuned absorptions and emissions of BOIDPY dyes to red, deep red and near infrared regions via significant extension of π-conjugation of BODIPY dyes by condensation reactions of aromatic aldehydes with 2,6-diformyl BODIPY dyes at 1,3,5,7-positions. Based on the foundation that we built for enhancing water solubility and tuning wavelength, we have designed and developed a series of water-soluble, BODIPY-based fluorescent probes for sensitive and selective sensing and imaging of cyanide, Zn (II) ions, lysosomal pH and cancer cells. We have developed three BODIPY-based fluorescent probes for sensing of cyanide ions by incorporating indolium moieties onto the 6-position of TEG- or BEG-modified BOIDPY dyes. Two of them are highly water-soluble. These fluorescent probes showed selective and fast ratiometric fluorescent responses to cyanide ions with a dramatic fluorescence color change from red to green accompanying a significant increase in fluorescent intensity. The detection limit was measured as 0.5 mM of cyanide ions. We also have prepared three highly water-soluble fluorescent probes for sensing of Zn (II) ions by introducing dipicoylamine (DPA, Zn ion chelator) onto 2- and/or 6-positions of BEG-modified BODIPY dyes. These probes showed selective and sensitive responses to Zn (II) ion in the range from 0.5 mM to 24 mM in aqueous solution at pH 7.0. Particularly, one of the probes displayed ratiometric responses to Zn (II) ions with fluorescence quenching at 661 nm and fluorescence enhancement at 521 nm. This probe has been successfully applied to the detection of intracellular Zn (II) ions inside the living cells. Then, we have further developed three acidotropic, near infrared emissive BODIPY- based fluorescent probes for detection of lysosomal pH by incorporating piperazine moiety at 3,5-positions of TEG- or BEG-modified BODIPY dyes as parts of conjugation. The probes have low auto-fluorescence at physiological neutral condition while their fluorescence intensities will significant increase at 715 nm when pH shift to acidic condition. These three probes have been successfully applied to the in vitro imaging of lysosomes inside two types of living cells. At the end, we have synthesized one water- soluble, near infrared emissive cancer cell targetable BODIPY-based fluorescent polymer bearing cancer homing peptide (cRGD) residues for cancer cell imaging applications. This polymer exhibited excellent water-solubility, near infrared emission (712 nm), good biocompatibility. It also showed low nonspecific interactions to normal endothelial cells and can effectively detect breast tumor cells.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

NON-CHROMATOGRAPHIC PURIFICATION OF SYNTHETIC BIO-OLIGOMERS

Synthetic oligonucleotides and peptides have found wide applications in industry and academic research labs. There are ~60 peptide drugs on the market and over 500 under development. The global annual sale of peptide drugs in 2010 was estimated to be $13 billion. There are three oligonucleotide-based drugs on market; among them, the FDA newly approved Kynamro was predicted to have a $100 million annual sale. The annual sale of oligonucleotides to academic labs was estimated to be $700 million. Both bio-oligomers are mostly synthesized on automated synthesizers using solid phase synthesis technology, in which nucleoside or amino acid monomers are added sequentially until the desired full-length sequence is reached. The additions cannot be complete, which generates truncated undesired failure sequences. For almost all applications, these impurities must be removed. The most widely used method is HPLC. However, the method is slow, expensive, labor-intensive, not amendable for automation, difficult to scale up, and unsuitable for high throughput purification. It needs large capital investment, and consumes large volumes of harmful solvents. The purification costs are estimated to be more than 50% of total production costs. Other methods for bio-oligomer purification also have drawbacks, and are less favored than HPLC for most applications. To overcome the problems of known biopolymer purification technologies, we have developed two non-chromatographic purification methods. They are (1) catching failure sequences by polymerization, and (2) catching full-length sequences by polymerization. In the first method, a polymerizable group is attached to the failure sequences of the bio-oligomers during automated synthesis; purification is achieved by simply polymerizing the failure sequences into an insoluble gel and extracting full-length sequences. In the second method, a polymerizable group is attached to the full-length sequences, which are then incorporated into a polymer; impurities are removed by washing, and pure product is cleaved from polymer. These methods do not need chromatography, and all drawbacks of HPLC no longer exist. Using them, purification is achieved by simple manipulations such as shaking and extraction. Therefore, they are suitable for large scale purification of oligonucleotide and peptide drugs, and also ideal for high throughput purification, which currently has a high demand for research projects involving total gene synthesis. The dissertation will present the details about the development of the techniques. Chapter 1 will make an introduction to oligodeoxynucleotides (ODNs), their synthesis and purification. Chapter 2 will describe the detailed studies of using the catching failure sequences by polymerization method to purify ODNs. Chapter 3 will describe the further optimization of the catching failure sequences by polymerization ODN purification technology to the level of practical use. Chapter 4 will present using the catching full-length sequence by polymerization method for ODN purification using acid-cleavable linker. Chapter 5 will make an introduction to peptides, their synthesis and purification. Chapter 6 will describe the studies using the catching full-length sequence by polymerization method for peptide purification.

DIMENSION REDUCTION FOR POWER SYSTEM MODELING USING PCA METHODS CONSIDERING INCOMPLETE DATA READINGS

Principal Component Analysis (PCA) is a popular method for dimension reduction that can be used in many fields including data compression, image processing, exploratory data analysis, etc. However, traditional PCA method has several drawbacks, since the traditional PCA method is not efficient for dealing with high dimensional data and cannot be effectively applied to compute accurate enough principal components when handling relatively large portion of missing data. In this report, we propose to use EM-PCA method for dimension reduction of power system measurement with missing data, and provide a comparative study of traditional PCA and EM-PCA methods. Our extensive experimental results show that EM-PCA method is more effective and more accurate for dimension reduction of power system measurement data than traditional PCA method when dealing with large portion of missing data set.

EVALUATION OF POTENTIAL TRANSLOAD FACILITY LOCATIONS IN THE UPPER PENINSULA (UP) OF MICHIGAN

Shippers want to improve their transportation efficiency and rail transportation has the potential to provide an economical alternative to trucking, but it also has potential drawbacks. The pressure to optimize transportation supply chain logistics has resulted in growing interest in multimodal alternatives, such as a combination of truck and rail transportation, but the comparison of multimodal and modal alternatives can be complicated. Shippers in Michigan’s Upper Peninsula (UP) face similar challenges. Adding to the challenge is the distance from major markets and the absence of available facilities for transloading activities. This study reviewed three potential locations for a transload facility (Nestoria, Ishpeming, and Amasa) where truck shipments could be transferred to rail and vice versa. These locations were evaluated on the basis of transportation costs for shippers when compared to the use of single mode transportation by truck to Wisconsin, Chicago, Minneapolis, and Sault Ste. Marie. In addition to shipping costs, the study also evaluated the potential impact of future carbon emission penalties on the shipping cost and the effects of changing fuel prices on shipping cost. The study used data obtained from TRANSEARCH database (2009) and found that although there were slight differences between percent savings for the three locations, any of them could provide potential benefits for movements to Chicago and Minneapolis, as long as final destination could be accessed by rail for delivery. Short haul movements of less than 200 miles (Wisconsin and Sault Ste. Marie) were not cost effective for multimodal transport. The study also found that for every dollar increase in fuel price, cost savings from multimodal option increased by three to five percent, but the inclusion of emission costs would only add one to two percent additional savings. Under a specific case study that addressed shipments by Northern Hardwoods, the most distant locations in Wisconsin would also provide cost savings, partially due to the possibility of using Michigan trucks with higher carrying capacity for the initial movement from the facility to transload location. In addition, Minneapolis movements were found to provide savings for Northern Hardwoods, even without final rail access.